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Predicting and Characterising Protein-Protein Complexes
Predicting and Characterising Protein-Protein Complexes Iain Hervé Moal June 2011 Biomolecular Modelling Laboratory, Cancer Research UK London Research Institute and Department of Biochemistry and Molecular Biology, University College London A thesis submitted in partial fulfilment of the requirements for the degree of Doctor of Philosophy in Biochemistry at the University College London. 2 I, Iain Hervé Moal, confirm that the work presented in this thesis is my own. Where information has been derived from other sources, I confirm that this has been indicated in the thesis. Abstract Macromolecular interactions play a key role in all life processes. The con- struction and annotation of protein interaction networks is pivotal for the understanding of these processes, and how their perturbation leads to dis- ease. However the extent of the human interactome and the limitations of the experimental techniques which can be brought to bear upon it necessit- ate theoretical approaches. Presented here are computational investigations into the interactions between biological macromolecules, focusing on the structural prediction of interactions, docking, and their kinetic and thermo- dynamic characterisation via empirical functions. Firstly, the use of normal modes in docking is investigated. Vibrational analysis of proteins are shown to indicate the motions which proteins are intrinsically disposed to under- take, and the use of this information to model flexible deformations upon protein-protein binding is evaluated. Subsequently SwarmDock, a docking algorithm which models flexibility as a linear combination of normal modes, is presented and benchmarked on a wide variety of test cases. This algorithm utilises state of the art energy functions and metaheuristics to navigate the free energy landscape. -
Functional Effects Detailed Research Plan
GeCIP Detailed Research Plan Form Background The Genomics England Clinical Interpretation Partnership (GeCIP) brings together researchers, clinicians and trainees from both academia and the NHS to analyse, refine and make new discoveries from the data from the 100,000 Genomes Project. The aims of the partnerships are: 1. To optimise: • clinical data and sample collection • clinical reporting • data validation and interpretation. 2. To improve understanding of the implications of genomic findings and improve the accuracy and reliability of information fed back to patients. To add to knowledge of the genetic basis of disease. 3. To provide a sustainable thriving training environment. The initial wave of GeCIP domains was announced in June 2015 following a first round of applications in January 2015. On the 18th June 2015 we invited the inaugurated GeCIP domains to develop more detailed research plans working closely with Genomics England. These will be used to ensure that the plans are complimentary and add real value across the GeCIP portfolio and address the aims and objectives of the 100,000 Genomes Project. They will be shared with the MRC, Wellcome Trust, NIHR and Cancer Research UK as existing members of the GeCIP Board to give advance warning and manage funding requests to maximise the funds available to each domain. However, formal applications will then be required to be submitted to individual funders. They will allow Genomics England to plan shared core analyses and the required research and computing infrastructure to support the proposed research. They will also form the basis of assessment by the Project’s Access Review Committee, to permit access to data. -
Development of Novel Strategies for Template-Based Protein Structure Prediction
Imperial College London Department of Life Sciences PhD Thesis Development of novel strategies for template-based protein structure prediction Stefans Mezulis supervised by Prof. Michael Sternberg Prof. William Knottenbelt September 2016 Abstract The most successful methods for predicting the structure of a protein from its sequence rely on identifying homologous sequences with a known struc- ture and building a model from these structures. A key component of these homology modelling pipelines is a model combination method, responsible for combining homologous structures into a coherent whole. Presented in this thesis is poing2, a model combination method using physics-, knowledge- and template-based constraints to assemble proteins us- ing information from known structures. By combining intrinsic bond length, angle and torsional constraints with long- and short-range information ex- tracted from template structures, poing2 assembles simplified protein models using molecular dynamics algorithms. Compared to the widely-used model combination tool MODELLER, poing2 is able to assemble models of ap- proximately equal quality. When supplied only with poor quality templates or templates that do not cover the majority of the query sequence, poing2 significantly outperforms MODELLER. Additionally presented in this work is PhyreStorm, a tool for quickly and accurately aligning the three-dimensional structure of a query protein with the Protein Data Bank (PDB). The PhyreStorm web server provides comprehensive, current and rapid structural comparisons to the protein data bank, providing researchers with another tool from which a range of biological insights may be drawn. By partitioning the PDB into clusters of similar structures and performing an initial alignment to the representatives of each cluster, PhyreStorm is able to quickly determine which structures should be excluded from the alignment. -
120421-24Recombschedule FINAL.Xlsx
Friday 20 April 18:00 20:00 REGISTRATION OPENS in Fira Palace 20:00 21:30 WELCOME RECEPTION in CaixaForum (access map) Saturday 21 April 8:00 8:50 REGISTRATION 8:50 9:00 Opening Remarks (Roderic GUIGÓ and Benny CHOR) Session 1. Chair: Roderic GUIGÓ (CRG, Barcelona ES) 9:00 10:00 Richard DURBIN The Wellcome Trust Sanger Institute, Hinxton UK "Computational analysis of population genome sequencing data" 10:00 10:20 44 Yaw-Ling Lin, Charles Ward and Steven Skiena Synthetic Sequence Design for Signal Location Search 10:20 10:40 62 Kai Song, Jie Ren, Zhiyuan Zhai, Xuemei Liu, Minghua Deng and Fengzhu Sun Alignment-Free Sequence Comparison Based on Next Generation Sequencing Reads 10:40 11:00 178 Yang Li, Hong-Mei Li, Paul Burns, Mark Borodovsky, Gene Robinson and Jian Ma TrueSight: Self-training Algorithm for Splice Junction Detection using RNA-seq 11:00 11:30 coffee break Session 2. Chair: Bonnie BERGER (MIT, Cambrige US) 11:30 11:50 139 Son Pham, Dmitry Antipov, Alexander Sirotkin, Glenn Tesler, Pavel Pevzner and Max Alekseyev PATH-SETS: A Novel Approach for Comprehensive Utilization of Mate-Pairs in Genome Assembly 11:50 12:10 171 Yan Huang, Yin Hu and Jinze Liu A Robust Method for Transcript Quantification with RNA-seq Data 12:10 12:30 120 Zhanyong Wang, Farhad Hormozdiari, Wen-Yun Yang, Eran Halperin and Eleazar Eskin CNVeM: Copy Number Variation detection Using Uncertainty of Read Mapping 12:30 12:50 205 Dmitri Pervouchine Evidence for widespread association of mammalian splicing and conserved long range RNA structures 12:50 13:10 169 Melissa Gymrek, David Golan, Saharon Rosset and Yaniv Erlich lobSTR: A Novel Pipeline for Short Tandem Repeats Profiling in Personal Genomes 13:10 13:30 217 Rory Stark Differential oestrogen receptor binding is associated with clinical outcome in breast cancer 13:30 15:00 lunch break Session 3. -
Python for Bioinformatics, Second Edition
PYTHON FOR BIOINFORMATICS SECOND EDITION CHAPMAN & HALL/CRC Mathematical and Computational Biology Series Aims and scope: This series aims to capture new developments and summarize what is known over the entire spectrum of mathematical and computational biology and medicine. It seeks to encourage the integration of mathematical, statistical, and computational methods into biology by publishing a broad range of textbooks, reference works, and handbooks. The titles included in the series are meant to appeal to students, researchers, and professionals in the mathematical, statistical and computational sciences, fundamental biology and bioengineering, as well as interdisciplinary researchers involved in the field. The inclusion of concrete examples and applications, and programming techniques and examples, is highly encouraged. Series Editors N. F. Britton Department of Mathematical Sciences University of Bath Xihong Lin Department of Biostatistics Harvard University Nicola Mulder University of Cape Town South Africa Maria Victoria Schneider European Bioinformatics Institute Mona Singh Department of Computer Science Princeton University Anna Tramontano Department of Physics University of Rome La Sapienza Proposals for the series should be submitted to one of the series editors above or directly to: CRC Press, Taylor & Francis Group 3 Park Square, Milton Park Abingdon, Oxfordshire OX14 4RN UK Published Titles An Introduction to Systems Biology: Statistical Methods for QTL Mapping Design Principles of Biological Circuits Zehua Chen Uri Alon -
Centre for Bioinformatics Imperial College London
Centre for Bioinformatics Imperial College London Inaugural Report January 2003 Centre Director: Prof Michael Sternberg www.imperial.ac.uk/bioinformatics [email protected] Support Service Head: Dr Sarah Butcher www.codon.bioinformatics.ic.ac.uk [email protected] Centre for Bioinformatics - Imperial College London - Inaugural Report - January 2003 1 Contents Summary..................................................................................................................... 3 1. Background and Objectives .................................................................................... 4 1.1 Background ....................................................................................................... 4 1.2 Objectives of the Centre for Bioinformatics ....................................................... 4 1.3 Objectives of the Bioinformatics Support Service.............................................. 5 1.4 Historical Notes ................................................................................................. 5 2. Management ........................................................................................................... 6 3. Biographies of the Team......................................................................................... 7 4. Bioinformatics Research at Imperial ....................................................................... 8 4.1 Affiliates of the Centre ....................................................................................... 8 4.2 Research Grants -
Centre for Bioinformatics Imperial College London Second Report 31
Centre for Bioinformatics Imperial College London Second Report 31 May 2004 Centre Director: Prof Michael Sternberg www.imperial.ac.uk/bioinformatics [email protected] Support Service Head: Dr Sarah Butcher www.codon.bioinformatics.ic.ac.uk [email protected] Centre for Bioinformatics - Imperial College London - Second Report - May 2004 1 Contents Summary..................................................................................................................... 3 1. Background and Objectives .................................................................................. 4 1.1 Objectives of the Report........................................................................................ 4 1.2 Background........................................................................................................... 4 1.3 Objectives of the Centre for Bioinformatics........................................................... 5 1.4 Objectives of the Bioinformatics Support Service ................................................. 5 2. Management ......................................................................................................... 6 3. Biographies of the Team....................................................................................... 7 4. Bioinformatics Research at Imperial ..................................................................... 8 4.1 Affiliates of the Centre........................................................................................... 8 4.2 Research.............................................................................................................. -
F. Alex Feltus, Ph.D
F. Alex Feltus, Ph.D. Curriculum Vitae 001010101000001000100001011001010101001000101001010010000100001010101001001000010010001000100001010001001010100100010001000101001000011110101000110010100010101010101010110101010100001000010010101010100100100000101001010010001010110100010 Clemson University • Department of Genetics & Biochemistry Biosystems Research Complex Rm 302C • 105 Collings St. • Clemson, SC 29634 (864)656-3231 (office) • (864) 654-5403 (home) • Skype: alex.feltus • [email protected] https://www.clemson.edu/science/departments/genetics-biochemistry/people/profiles/ffeltus https://orcid.org/0000-0002-2123-6114 https://www.linkedin.com/in/alex-feltus-86a0073a 001010101000001010101010101010101010100110000101100101010100100010100101001000010000101010100100100001001000100010000101000100101010010001000100010100100001111010100011001010001000001000010010101010100100100000101001010010001010110100010 Educational Background: Ph.D. Cell Biology (2000) Vanderbilt University (Nashville, TN) B.Sc. Biochemistry (1992) Auburn University (Auburn, AL) Ph.D. Dissertation Title: Transcriptional Regulation of Human Type II 3β-Hydroxysteroid Dehydrogenase: Stat5- Centered Control by Steroids, Prolactin, EGF, and IL-4 Hormones. Professional Experience: 2018- Professor, Clemson University Department of Genetics and Biochemistry 2017- Core Faculty, Biomedical Data Science and Informatics (BDSI) PhD Program 2018- Faculty Member, Clemson Center for Human Genetics 2020- Faculty Scholar, Clemson University School of Health Research (CUSHR) 2019- co-Founder, -
ACM-BCB 2016 the 7Th ACM Conference on Bioinformatics
ACM-BCB 2016 The 7th ACM Conference on Bioinformatics, Computational Biology, and Health Informatics October 2-5, 2016 Organizing Committee General Chairs: Steering Committee: Ümit V. Çatalyürek, Georgia Institute of Technology Aidong Zhang, State University of NeW York at Buffalo, Genevieve Melton-Meaux, University of Minnesota Co-Chair May D. Wang, Georgia Institute of Technology and Program Chairs: Emory University, Co-Chair John Kececioglu, University of Arizona Srinivas Aluru, Georgia Institute of Technology Adam Wilcox, University of Washington Tamer Kahveci, University of Florida Christopher C. Yang, Drexel University Workshop Chair: Ananth Kalyanaraman, Washington State University Tutorial Chair: Mehmet Koyuturk, Case Western Reserve University Demo and Exhibit Chair: Robert (Bob) Cottingham, Oak Ridge National Laboratory Poster Chairs: Lin Yang, University of Florida Dongxiao Zhu, Wayne State University Registration Chair: Preetam Ghosh, Virginia CommonWealth University Publicity Chairs Daniel Capurro, Pontificia Univ. Católica de Chile A. Ercument Cicek, Bilkent University Pierangelo Veltri, U. Magna Graecia of Catanzaro Student Travel Award Chairs May D. Wang, Georgia Institute of Technology and Emory University JaroslaW Zola, University at Buffalo, The State University of NeW York Student Activity Chair Marzieh Ayati, Case Western Reserve University Dan DeBlasio, Carnegie Mellon University Proceedings Chairs: Xinghua Mindy Shi, U of North Carolina at Charlotte Yang Shen, Texas A&M University Web Admins: Anas Abu-Doleh, The -
Spinout Equinox Pharma Speeds up and Reduces the Cost of Drug Discovery
Spinout Equinox Pharma speeds up and reduces the cost of drug discovery pinout Equinox Pharma1 provides a service to the pharma and biopharma industries that helps in the development of new drugs. The company, established by researchers from Imperial College London in IMPACT SUMMARY 2008, is using its own proprietary software to help speed up and reduce the cost of discovery processes. S Spinout Equinox Pharma provides services to the agri- tech and pharmaceuticals industries to accelerate the Equinox is based on BBSRC-funded collaborative research The technology also has applications in the agrochemical discovery of molecules that could form the basis of new conducted by Professors Stephen Muggleton2, Royal sector, and is being used by global agri-tech company products such as drugs or herbicides. Academy Chair in Machine Learning, Mike Sternberg3, Chair Syngenta. The company arose from BBSRC bioinformatics and of Structural Bioinformatics, and Paul Freemont4, Chair of structural biology research at Imperial College London. Protein Crystallography, at Imperial College London. “The power of a logic-based approach is that it can Technology commercialisation company NetScientific propose chemically-novel molecules that can have Ltd has invested £250K in Equinox. The technology developed by the company takes a logic- enhanced properties and are able to be the subject of novel Equinox customers include major pharmaceutical based approach to discover novel drugs, using computers to ‘composition of matter’ patents,” says Muggleton. companies such as Japanese pharmaceutical company learn from a set of biologically-active molecules. It combines Astellas and agro chemical companies such as knowledge about traditional drug discovery methods and Proving the technology Syngenta, as well as SMEs based in the UK, Europe, computer-based analyses, and focuses on the key stages in A three-year BBSRC grant in 2003 funded the work of Japan and the USA. -
Optical Maps in Guided Genome Assembly
Optical maps in guided genome assembly Miika Leinonen Helsinki September 9, 2019 UNIVERSITY OF HELSINKI Master’s Programme in Computer Science HELSINGIN YLIOPISTO — HELSINGFORS UNIVERSITET — UNIVERSITY OF HELSINKI Tiedekunta — Fakultet — Faculty Koulutusohjelma — Studieprogram — Study Programme Faculty of Science Study Programme in Computer Science Tekijä — Författare — Author Miika Leinonen Työn nimi — Arbetets titel — Title Optical maps in guided genome assembly Ohjaajat — Handledare — Supervisors Leena Salmela and Veli Mäkinen Työn laji — Arbetets art — Level Aika — Datum — Month and year Sivumäärä — Sidoantal — Number of pages Master’s thesis September 9, 2019 41 pages + 0 appendices Tiivistelmä — Referat — Abstract With the introduction of DNA sequencing over 40 years ago, we have been able to take a peek at our genetic material. Even though we have had a long time to develop sequencing strategies further, we are still unable to read the whole genome in one go. Instead, we are able to gather smaller pieces of the genetic material, which we can then use to reconstruct the original genome with a process called genome assembly. As a result of the genome assembly we often obtain multiple long sequences representing different regions of the genome, which are called contigs. Even though a genome often consists of a few separate DNA molecules (chromosomes), the number of obtained contigs outnumbers them substantially, meaning our reconstruction of the genome is not perfect. The resulting contigs can afterwards be refined by ordering, orienting and scaffolding them using additional information about the genome, which is often done manually by hand. The assembly process can also be guided automatically with the additional information, and in this thesis we are introducing a method that utilizes optical maps to aid us assemble the genome more accurately. -
ISBRA 2012 Short Abstracts
1 ISBRA 20 2 SHORT ABSTRACTS 8TH INTERNATIONAL SYMPOSIUM ON BIOINFORMATICS RESEARCH AND APPLICATIONS May 21-23, 2012 University of Texas at Dallas, Dallas, TX http://www.cs.gsu.edu/isbra12/ Symposium Organizers Steering Committee Dan Gusfield, University of California, Davis Ion Mandoiu, University of Connecticutt Yi Pan, Georgia State University Marie-France Sagot, INRIA Alex Zelikovsky, Georgia State University General Chairs Ovidiu Daesku, University of Texas at Dallas Raj Sunderraman, Georgia State University Program Chairs Leonidas Bleris, University of Texas at Dallas Ion Mandoiu, University of Connecticut Russell Schwartz, Carnegie Mellon University Jianxin Wang, Central South University Publicity Chair Sahar Al Seesi, University of Connecticut Finance Chairs Anu Bourgeois, Georgia State University Raj Sunderraman, Georgia State University Web Master, Web Design Piyaphol Phoungphol J. Steven Kirtzic Sponsors NATIONAL SCIENCE DEPARTMENT OF COMPUTER SCIENCE DEPARTMENT OF COMPUTER SCIENCE FOUNDATION GEORGIA STATE UNIVESITY UNIVERSITY OF TEXAS AT DALLAS i Program Committee Members Srinivas Aluru, Iowa State University Allen Holder, Rose-Hulman Istitute of S. Cenk Sahinalp, Simon Fraser Danny Barash, Ben-Gurion Technology University University Jinling Huang, Eastern Carolina David Sankoff, University of Ottawa Robert Beiko, Dalhousie University University Russell Schwartz, Carnegie Mellon Anne Bergeron, Universite du Lars Kaderali, University of University Quebec a Montreal Heidelberg Joao Setubal, Virginia Bioinformatics Iyad Kanj,